A variety of video compression/decompression methods and compression/decompression hardware/firmware modules and software modules (“codecs”), including the Moving Picture Experts Group (“MPEG”) MPEG-1, MPEG-2, and MPEG-4 video coding standards and the more recent H.264 video coding standard, have been developed to code pixel-based and frame-based video signals into compressed bit streams, by lossy compression techniques, for compact storage in electronic, magnetic, and optical storage media, including DVDs and computer files, as well as for efficient transmission via cable television, satellite television, and the Internet. The compressed bit stream can be subsequently accessed, or received, and decompressed by a decoder in order to generate a reasonably high-fidelity reconstruction of the original pixel-based and frame-based video signal.
Because many of the currently available video coding methods have been designed for broadcast and distribution of compressed bit streams to a variety of relatively inexpensive, low-powered consumer devices, the currently available video coding methods generally tend to partition the total computational complexity of the coding-compression/decoding-decompression process so that coding, generally carried out once or a very few times by video distributors and broadcasters, is computationally complex and expensive, while decoding, generally carried out on relatively inexpensive, low-powered consumer devices, is computationally straightforward and inexpensive. However, with the emergence of a variety of hand-held video-recording consumer devices, including video cameras, cell phones, and other such hand-held, portable devices, a need has arisen for video codecs that place a relatively small computational burden on the coding/compression functionality within the hand-held video recording device, and a comparatively high computational burden on the decoding device, generally a high-powered server or other computationally well-endowed coded-video-signal-receiving entity. This division of computational complexity is referred to as “reversed computational complexity.”
A relatively extreme reversed-computational-complexity problem domain involves information collection and coding, by low-powered, computationally-constrained sensor devices interconnected by a wireless network, for transmission to high-end computer systems for decoding and subsequent processing. Designers, manufacturers, and users of computationally-constrained, low-power information sources, including the above-mentioned sensors, continue to seek improved information-coding and coded-information-decoding methods and systems that provide efficient coding and transmission of sensor-collected information through various electronic communications media to computer systems with relatively large computational bandwidths.